"""
Example analysis script - What you can do with the collected data
"""

import sqlite3
import json
import os
from collections import defaultdict

class StockAnalyzer:
    def __init__(self, db_path="data/stocks.db"):
        self.conn = sqlite3.connect(db_path)
        self.cursor = self.conn.cursor()
    
    def get_summary_stats(self):
        """Get overall statistics"""
        print("\n" + "=" * 70)
        print("DATABASE SUMMARY STATISTICS")
        print("=" * 70)
        
        # Total stocks
        self.cursor.execute("SELECT COUNT(*) FROM stocks_master")
        total_stocks = self.cursor.fetchone()[0]
        print(f"\nTotal stocks tracked: {total_stocks}")
        
        # By exchange
        self.cursor.execute("""
            SELECT exchange, COUNT(*) as count 
            FROM stocks_master 
            GROUP BY exchange 
            ORDER BY count DESC
        """)
        print("\nStocks by exchange:")
        for exchange, count in self.cursor.fetchall():
            print(f"  {exchange}: {count}")
        
        # By sector (if available)
        self.cursor.execute("""
            SELECT sector, COUNT(*) as count 
            FROM stocks_master 
            WHERE sector IS NOT NULL AND sector != ''
            GROUP BY sector 
            ORDER BY count DESC 
            LIMIT 10
        """)
        sectors = self.cursor.fetchall()
        if sectors:
            print("\nTop 10 sectors:")
            for sector, count in sectors:
                print(f"  {sector}: {count}")
        
        # Coverage stats
        self.cursor.execute("""
            SELECT 
                SUM(CASE WHEN has_financials = 1 THEN 1 ELSE 0 END) as with_financials,
                SUM(CASE WHEN has_news = 1 THEN 1 ELSE 0 END) as with_news,
                SUM(CASE WHEN has_press_releases = 1 THEN 1 ELSE 0 END) as with_pr,
                SUM(CASE WHEN has_financials = 1 AND has_news = 1 AND has_press_releases = 1 THEN 1 ELSE 0 END) as complete
            FROM coverage_report
        """)
        fin, news, pr, complete = self.cursor.fetchone()
        
        print("\nData coverage:")
        print(f"  Stocks with financials: {fin}")
        print(f"  Stocks with news: {news}")
        print(f"  Stocks with press releases: {pr}")
        print(f"  Fully covered stocks: {complete}")
    
    def find_recent_news_activity(self, limit=20):
        """Find stocks with most recent news"""
        print("\n" + "=" * 70)
        print(f"TOP {limit} STOCKS BY NEWS ACTIVITY")
        print("=" * 70)
        
        # Load news files and count articles
        news_dir = "data/news"
        if not os.path.exists(news_dir):
            print("No news data available yet")
            return
        
        stock_news_count = []
        
        for filename in os.listdir(news_dir):
            if filename.endswith('_news_pr.json'):
                ticker = filename.replace('_news_pr.json', '')
                filepath = os.path.join(news_dir, filename)
                
                with open(filepath, 'r') as f:
                    data = json.load(f)
                    news_count = len(data.get('news_articles', []))
                    pr_count = len(data.get('press_releases', []))
                    
                    if news_count > 0 or pr_count > 0:
                        stock_news_count.append({
                            'ticker': ticker,
                            'news': news_count,
                            'pr': pr_count,
                            'total': news_count + pr_count
                        })
        
        # Sort by total
        stock_news_count.sort(key=lambda x: x['total'], reverse=True)
        
        print(f"\n{'Ticker':<10} {'News':<10} {'PR':<10} {'Total':<10}")
        print("-" * 40)
        for stock in stock_news_count[:limit]:
            print(f"{stock['ticker']:<10} {stock['news']:<10} {stock['pr']:<10} {stock['total']:<10}")
    
    def find_stocks_by_sector(self, sector):
        """Find all stocks in a sector"""
        print("\n" + "=" * 70)
        print(f"STOCKS IN SECTOR: {sector.upper()}")
        print("=" * 70)
        
        self.cursor.execute("""
            SELECT symbol, company_name, exchange 
            FROM stocks_master 
            WHERE sector LIKE ? 
            ORDER BY symbol
        """, (f"%{sector}%",))
        
        stocks = self.cursor.fetchall()
        
        if stocks:
            print(f"\nFound {len(stocks)} stocks:")
            for symbol, name, exchange in stocks:
                print(f"  {symbol:<8} {name:<50} [{exchange}]")
        else:
            print(f"\nNo stocks found in sector: {sector}")
    
    def get_stock_report(self, ticker):
        """Get full report for a stock"""
        print("\n" + "=" * 70)
        print(f"STOCK REPORT: {ticker}")
        print("=" * 70)
        
        # Get basic info
        self.cursor.execute("""
            SELECT company_name, exchange, sector, industry, listing_date 
            FROM stocks_master 
            WHERE symbol = ?
        """, (ticker,))
        
        result = self.cursor.fetchone()
        if not result:
            print(f"\nStock {ticker} not found in database")
            return
        
        name, exchange, sector, industry, listing_date = result
        
        print(f"\nCompany: {name}")
        print(f"Exchange: {exchange}")
        if sector:
            print(f"Sector: {sector}")
        if industry:
            print(f"Industry: {industry}")
        if listing_date:
            print(f"Listing Date: {listing_date}")
        
        # Check coverage
        self.cursor.execute("""
            SELECT has_financials, has_news, has_press_releases 
            FROM coverage_report 
            WHERE ticker = ?
        """, (ticker,))
        
        coverage = self.cursor.fetchone()
        if coverage:
            has_fin, has_news, has_pr = coverage
            print(f"\nData Coverage:")
            print(f"  Financials: {'✅' if has_fin else '❌'}")
            print(f"  News: {'✅' if has_news else '❌'}")
            print(f"  Press Releases: {'✅' if has_pr else '❌'}")
        
        # Load financial data if available
        fin_file = f"data/financials/{ticker}_yahoo.json"
        if os.path.exists(fin_file):
            print(f"\nFinancial Data: (see {fin_file})")
            with open(fin_file, 'r') as f:
                data = json.load(f)
                if data.get('profile', {}).get('current_price'):
                    print(f"  Current Price: ${data['profile']['current_price']}")
        
        # Load news if available
        news_file = f"data/news/{ticker}_news_pr.json"
        if os.path.exists(news_file):
            with open(news_file, 'r') as f:
                data = json.load(f)
                news_count = len(data.get('news_articles', []))
                pr_count = len(data.get('press_releases', []))
                print(f"\nNews & Press Releases:")
                print(f"  News articles: {news_count}")
                print(f"  Press releases: {pr_count}")
                
                if news_count > 0:
                    print(f"\n  Recent news:")
                    for article in data['news_articles'][:3]:
                        print(f"    - {article.get('title', 'N/A')}")
        
        # Check if report exists
        report_file = f"data/reports/{ticker}_report.txt"
        if os.path.exists(report_file):
            print(f"\nFull report available at: {report_file}")
    
    def export_to_csv(self, output_file="stock_list.csv"):
        """Export stock list to CSV"""
        print("\n" + "=" * 70)
        print(f"EXPORTING TO CSV: {output_file}")
        print("=" * 70)
        
        self.cursor.execute("""
            SELECT s.symbol, s.company_name, s.exchange, s.sector, s.industry,
                   c.has_financials, c.has_news, c.has_press_releases
            FROM stocks_master s
            LEFT JOIN coverage_report c ON s.symbol = c.ticker
            ORDER BY s.symbol
        """)
        
        import csv
        with open(output_file, 'w', newline='', encoding='utf-8') as f:
            writer = csv.writer(f)
            writer.writerow(['Symbol', 'Company', 'Exchange', 'Sector', 'Industry', 
                           'Has Financials', 'Has News', 'Has PR'])
            writer.writerows(self.cursor.fetchall())
        
        print(f"\n✅ Exported to {output_file}")
    
    def close(self):
        self.conn.close()


def main():
    """Example usage"""
    print("\n" + "=" * 70)
    print("STOCK DATA ANALYSIS - EXAMPLES")
    print("=" * 70)
    
    # Check if database exists
    if not os.path.exists("data/stocks.db"):
        print("\n❌ Database not found!")
        print("   Run 'python main.py' first to collect data")
        return
    
    analyzer = StockAnalyzer()
    
    # Example 1: Get summary statistics
    analyzer.get_summary_stats()
    
    # Example 2: Find most active stocks (by news)
    analyzer.find_recent_news_activity(limit=10)
    
    # Example 3: Find stocks in a sector
    # analyzer.find_stocks_by_sector("Technology")
    
    # Example 4: Get report for specific stock
    # analyzer.get_stock_report("ABC")
    
    # Example 5: Export to CSV
    # analyzer.export_to_csv("my_stocks.csv")
    
    analyzer.close()
    
    print("\n" + "=" * 70)
    print("ANALYSIS COMPLETE")
    print("=" * 70)
    print("\nYou can modify this script to:")
    print("  - Filter stocks by criteria (P/E, market cap, etc.)")
    print("  - Find stocks with specific keywords in news")
    print("  - Compare stocks within sectors")
    print("  - Track changes over time")
    print("  - Generate custom reports")


if __name__ == "__main__":
    main()